46 results
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**Nonlinear functional causal models for distinguishing cause from effect**
In *Statistics and Causality: Methods for Applied Empirical Research*, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)

**A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis**
In *Brain-Computer Interfaces: Lab Experiments to Real-World Applications*, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)

**Tractable Structured Prediction using the Permutohedral Lattice**
ETH Zurich, 2016 (phdthesis)

**Advances in computational imaging: Benchmarking Deblurring Algorithms, Deep Neural Inpainting, Depth Estimation from Light Fields**
Eberhard Karls Universität Tübingen, Germany, 2016 (phdthesis)

**Screening Rules for Convex Problems**
2016 (unpublished) Submitted

**easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies**
Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

**Causal Discovery Beyond Conditional Independences**
Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

**From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding**
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

**Machine Learning Approaches to Image Deconvolution**
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

**Kernel methods in medical imaging**
In *Handbook of Biomedical Imaging*, pages: 63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (inbook)

**Blind Retrospective Motion Correction of MR Images**
University of Tübingen, Germany, May 2015 (phdthesis)

**Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data**
In *Visualization and Processing of Higher Order Descriptors for Multi-Valued Data*, pages: 299-319, (Editors: Hotz, I. and Schultz, T.), Springer, 2015 (inbook)

**A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**Sequential Image Deconvolution Using Probabilistic Linear Algebra**
Technical University of Munich, Germany, 2015 (mastersthesis)

**Causal Inference in Neuroimaging**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**The effect of frowning on attention**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**Justifying Information-Geometric Causal Inference**
In *Measures of Complexity: Festschrift for Alexey Chervonenkis*, pages: 253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (inbook)

**Projected Newton-type methods in machine learning**
In *Optimization for Machine Learning*, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)

**Optimization for Machine Learning**
pages: 494, Neural information processing series, MIT Press, Cambridge, MA, USA, December 2011 (book)

**Bayesian Time Series Models**
pages: 432, Cambridge University Press, Cambridge, UK, August 2011 (book)

**Statistical Learning Theory: Models, Concepts, and Results**
In *Handbook of the History of Logic, Vol. 10: Inductive Logic*, 10, pages: 651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 (inbook)

**Crowdsourcing for optimisation of deconvolution methods via an iPhone application**
Hochschule Reutlingen, Germany, April 2011 (mastersthesis)

**Learning functions with kernel methods**
University of Pavia, Italy, January 2011 (phdthesis)

**Robot Learning**
In *Encyclopedia of Machine Learning*, pages: 865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 (inbook)

**What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI**
In *Affective Computing and Intelligent Interaction*, 6975, pages: 447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 (inbook)

**Handbook of Statistical Bioinformatics**
pages: 627, Springer Handbooks of Computational Statistics, Springer, Berlin, Germany, 2011 (book)

**Kernel Methods in Bioinformatics **
In *Handbook of Statistical Bioinformatics*, pages: 317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 (inbook)

**Cue Combination: Beyond Optimality**
In *Sensory Cue Integration*, pages: 144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 (inbook)

**Model Learning in Robot Control**
Albert-Ludwigs-Universität Freiburg, Germany, 2011 (phdthesis)

**Extension to Kernel Dependency Estimation with Applications to Robotics**
Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

**Geometrical aspects of statistical learning theory**
Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

**Implicit Surfaces For Modelling
Human Heads**
Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

**Machine Learning Methods for Brain-Computer Interdaces**
Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

**Liver Perfusion using Level Set Methods**
Biologische Kybernetik, Shanghai JiaoTong University, Shanghai, China, July 2005 (diplomathesis)

**Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain**
Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005 (diplomathesis)

**Discriminative Methods for Label Sequence Learning**
Brown University, Providence, RI, USA, May 2005 (phdthesis)

**Support Vector Classification of Images with Local Features**
Biologische Kybernetik, University of Massachusetts, Amherst, May 2005 (diplomathesis)

**Efficient Pattern Selection for Support Vector Classifiers and its CRM Application**
Biologische Kybernetik, Seoul National University, Seoul, Korea, February 2005 (phdthesis)

**Kernels: Regularization and Optimization**
Biologische Kybernetik, The Australian National University, Canberra, Australia, 2005 (phdthesis)

**Support Vector Machines and Kernel Algorithms**
In *Encyclopedia of Biostatistics (2nd edition), Vol. 8*, 8, pages: 5328-5335, (Editors: P Armitage and T Colton), John Wiley & Sons, NY USA, 2005 (inbook)

**Visual perception
I: Basic principles**
In *Handbook of Cognition*, pages: 3-47, (Editors: Lamberts, K. , R. Goldstone), Sage, London, 2005 (inbook)

**Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond**
pages: 644, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, December 2002, Parts of this book, including an introduction to kernel methods, can be downloaded here. (book)

**Nonlinear Multivariate Analysis with Geodesic Kernels**
Biologische Kybernetik, Technische Universität Berlin, February 2002 (diplomathesis)

**Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms**
Biologische Kybernetik, Ecole Polytechnique, 2002 (phdthesis) Accepted

**Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge**
Biologische Kybernetik, 2002 (phdthesis)

**Support vector learning**
pages: 173, Oldenbourg, München, Germany, 1997, Zugl.: Berlin, Techn. Univ., Diss., 1997 (book)